Automated Discovery of CEP Applications with Evolutionary Computing
Saved in:
| Title: | Automated Discovery of CEP Applications with Evolutionary Computing |
|---|---|
| Authors: | Appetito, Giulio, Medvet, Eric, Gulisano, Vincenzo Massimiliano, 1984 |
| Source: | Relaxed Semantics Across the Data Analytics Stack (RELAX-DN) 19th ACM International Conference on Distributed and Event-Based Systems, DEBS 2025 , Gothenburg, Sweden Debs 2025 Proceedings of the 19th ACM International Conference on Distributed and Event Based Systems. :33-38 |
| Subject Terms: | Complex Event Processing, Evolutionary Computing |
| Description: | Complex event processing (CEP) is key for detecting patterns in digital systems (e.g., smart grids and vehicular networks) through platforms like Apache Flink CEP that decouple application logic from distributed execution in cloud-to-edge infrastructures. Yet, a barrier remains: system experts can identify relevant patterns but often lack programming skills to implement CEP applications, limiting effective use.We present a preliminary study on using evolutionary computation to automate CEP application discovery from data. Experts provide examples of relevant event sequences for an evolutionary algorithm to evolve applications to detect similar patterns. Initial results are promising and highlight CEP-related challenges that open new research directions. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/547929 https://research.chalmers.se/publication/547929/file/547929_Fulltext.pdf |
| Database: | SwePub |
Nájsť tento článok vo Web of Science | Abstract: | Complex event processing (CEP) is key for detecting patterns in digital systems (e.g., smart grids and vehicular networks) through platforms like Apache Flink CEP that decouple application logic from distributed execution in cloud-to-edge infrastructures. Yet, a barrier remains: system experts can identify relevant patterns but often lack programming skills to implement CEP applications, limiting effective use.We present a preliminary study on using evolutionary computation to automate CEP application discovery from data. Experts provide examples of relevant event sequences for an evolutionary algorithm to evolve applications to detect similar patterns. Initial results are promising and highlight CEP-related challenges that open new research directions. |
|---|---|
| DOI: | 10.1145/3701717.3730548 |